8529 Background: KRASG12C inhibitors such as adagrasib and sotorasib have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients develop primary or secondary resistance. A biomarker of response to KRASG12C inhibitor is needed for better patient stratification and to understand the resistance mechanism. Methods: We analyzed transcriptional correlates of adagrasib treatment outcome in 68 patients in the KRYSTAL-1 trial, a phase 1/2 clinical trial of adagrasib monotherapy in the second line and beyond treatment for NSCLC. We also treated KRAS-mutated lung cancer mouse models and organoids with a KRAS inhibitor for the long term and characterized the resistant tumors’ transcriptional profile to identify resistance mechanisms. We also performed serial gene expression analysis of KrasG12D mutated lung organoids undergoing squamous transformation to identify transcription factor involved in the resistance process. Results: In patients with lung adenocarcinoma with KRASG12C and STK11/ LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids, treated with KRAS inhibitors adagrasib and MRTX1133, respectively, reveal that tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. We identify TP63 to be a transcription factor whose expression correlated with squamous transformation. The analysis of lineage plasticity program, adagrasib resistant tumors, and p63 regulon revealed KRT6A to be a common biomarker whose expression correlated with overall survival in the KRYSTAL-1 cohort. Conclusions: KRASG12C mutated lung adenocarcinoma patients with a higher expression of squamous cell carcinoma gene expression signature respond poorly to adagrasib treatment. Expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

Supplementary Figure Legends

KRASG12C inhibitors (adagrasib and sotorasib) have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients eventually develop resistance. In lung patients with adenocarcinoma with KRASG12C and STK11/LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids treated with KRAS inhibitors reveal tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. Transcriptomic and epigenomic analyses reveal ΔNp63 drives AST and modulates response to KRAS inhibition. We identify an intermediate high-plastic cell state marked by expression of an AST plasticity signature and Krt6a. Notably, expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

<p>Role of metabolic pathways imparting gemcitabine resistance in pancreatic cancer</p>

Supplementary Table S10 Differential gene expression analysis of scRNA-seq data from tumor cluster in patient #1778 (AMG-510-resistant tumor) vs patient #1566 (control, KRASG12V tumor)

Supplementary Table S11 Differential gene expression analysis of scRNA-seq data from tumor cluster in patient #2349 (MRTX-849/TNO155-resistant) vs patient #1566 (control, KRASG12V tumor)

<p>Effects of glutamine deprivation on cell viability and NRF2 expression</p>

<p>Isotype control for NRF2 in IHC and survival measure for NRF2</p>

Supplementary Table S8 RNA-seq analysis of MTRX-849/SHP099-resistant tumor nodules from KCL mice

Supplementary Table S7 RPPA from MTRX-849-resistant tumor nodules from KCL mice

Cell cycle analysis of PDAC cells upon NRF2 activation

PDF - 2607K, Ras-driven cancer cells are uniquely dependent on exogenous fatty acids.

Supplementary Table S3 RNA-seq analysis of H2030 and H2122 cells treated with MRTX-849 or vehicle for 48 hr

<p>Effects of NRF2 activation on metabolomics</p>

<p>Gemcitabine IC50 Values</p>

Abstract Non–small lung cancers (NSCLC) frequently (∼30%) harbor KRAS driver mutations, half of which are KRASG12C. KRAS-mutant NSCLC with comutated STK11 and/or KEAP1 is particularly refractory to conventional, targeted, and immune therapy. Development of KRASG12C inhibitors (G12Ci) provided a major therapeutic advance, but resistance still limits their efficacy. To identify genes whose deletion augments efficacy of the G12Cis adagrasib (MRTX-849) or adagrasib plus TNO155 (SHP2i), we performed genome-wide CRISPR/Cas9 screens on KRAS/STK11-mutant NSCLC lines. Recurrent, potentially targetable, synthetic lethal (SL) genes were identified, including serine–threonine kinases, tRNA-modifying and proteoglycan synthesis enzymes, and YAP/TAZ/TEAD pathway components. Several SL genes were confirmed by siRNA/shRNA experiments, and the YAP/TAZ/TEAD pathway was extensively validated in vitro and in mice. Mechanistic studies showed that G12Ci treatment induced gene expression of RHO paralogs and activators, increased RHOA activation, and evoked ROCK-dependent nuclear translocation of YAP. Mice and patients with acquired G12Ci- or G12Ci/SHP2i-resistant tumors showed strong overlap with SL pathways, arguing for the relevance of the screen results. These findings provide a landscape of potential targets for future combination strategies, some of which can be tested rapidly in the clinic. Significance: Identification of synthetic lethal genes with KRASG12C using genome-wide CRISPR/Cas9 screening and credentialing of the ability of TEAD inhibition to enhance KRASG12C efficacy provides a roadmap for combination strategies. See related commentary by Johnson and Haigis, p. 4005

Supplementary Table S1 MaGeCK analysis of MRTX-849 CRISPR/Cas9 SL screens of NSCLC cell lines

Supplementary Table S2 Overlapping dropouts (FDR <0.1) from MRTX-849 CRISPR/Cas9 screens in NSCLC cell lines

Supplementary Table S9 RPPA data from MRTX-849/SHP099-resistant tumor nodules in KCL mice

Supplementary Table S6 RNA-seq analysis of MTRX-849-resistant tumor nodules from KCL mice